scholarly journals Special Issue “Plug-In Hybrid Electric Vehicle (PHEV)”

2019 ◽  
Vol 9 (14) ◽  
pp. 2829
Author(s):  
Joeri Van Mierlo
Keyword(s):  
Electric Vehicles ◽  
Energy Efficient ◽  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Control Strategies ◽  
Special Issue ◽  
Power Flow Control ◽  
Power Electronics Converters ◽  
Hybrid Electric ◽  
Efficient Power

Climate change, urban air quality, and dependency on crude oil are important societal challenges. In the transportation sector especially, clean and energy-efficient technologies must be developed. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) have gained a growing interest in the vehicle industry. Nowadays, the commercialization of EVs and PHEVs has been possible in different applications (i.e., light duty, medium duty, and heavy duty vehicles) thanks to the advances in energy-storage systems, power electronics converters (including DC/DC converters, DC/AC inverters, and battery charging systems), electric machines, and energy efficient power flow control strategies. This Special Issue is focused on the recent advances in electric vehicles and (plug-in) hybrid vehicles that address the new powertrain developments and go beyond the state-of-the-art (SOTA).

scholarly journals SUBOPTIMAL SUPERVISORY LEVEL POWER FLOW CONTROL OF A HYBRID ELECTRIC VEHICLE

2005 ◽  
Vol 38 (1) ◽  
pp. 218-223 ◽  
Author(s):  
Kasemsak Uthaichana ◽  
Sorin Bengea ◽  
Raymond DeCarlo
Keyword(s):  
Flow Control ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Power Flow Control ◽  
Hybrid Electric

scholarly journals An Agent based Power Flow Control for Hybrid Electric Vehicles

2004 ◽  
Vol 37 (22) ◽  
pp. 481-488
Author(s):  
Lucio Ippolito ◽  
Vincenzo Loia ◽  
Pierluigi Siano
Keyword(s):  
Flow Control ◽  
Electric Vehicles ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Power Flow Control ◽  
Agent Based ◽  
Hybrid Electric

Power Flow Control in Hybrid Electric Vehicles

2011 ◽  
Author(s):  
Guillermo Becerra ◽  
Jose´ Luis Mendoza-Soto ◽  
Luis Alvarez-Icaza
Keyword(s):  
Flow Control ◽  
Fuel Consumption ◽  
Electric Vehicles ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Optimization Problems ◽  
Combustion Engine ◽  
Computational Cost ◽  
Power Flow Control ◽  
Hybrid Electric

In this paper a new strategy for controlling the power flow in hybrid electric vehicles is described. The strategy focuses in the planetary gear system where kinematic and dynamic constraints must be satisfied. The aim is to satisfy driver demands and to reduce fuel consumption. The resultant power flow control is continuous and uses the internal combustion engine with the maximum possible efficiency. The strategy is not optimal, although it is inspired by the solution to most optimization problems. The main advantages are that the computational cost is low, when compared to optimization based approaches, and that it is easy to tune. The strategy is tested with simulations using a mathematical model of a power train of a hybrid diesel-electric bus subjected to the power demands of representative urban area driving cycles. Simulation results indicate that the strategy achieves small speed tracking errors and attains good fuel consumption reduction levels.

scholarly journals Bidirectional Dc to DC Converter with Ann Controller for Hybrid Electric Vehicle

2019 ◽  
Vol 8 (12) ◽  
pp. 4446-4453
Keyword(s):  
Flow Control ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Power Flow Control ◽  
Loop Control ◽  
Dual Source ◽  
Hybrid Electric ◽  
Artificial Neural Network Ann ◽  
The One

A bidirectional chopper (BDC) is the one which can interface main source (HVS), auxiliary source (LVS) and a DCBus voltage at different levels which is implemented in Hybrid Electric Vehicle (HEV). This converter operation is of two modes namely dual source powering mode and energy re generation mode along with power flow control in both the directions. And also the independent power flow control across two sources (i.e. the dual source buck-boost mode). The operation, closed loop control of artificial neural network (ANN) and the comparison between PI and ANN control are provided in simulation results.

Multi-Lookup Table Based Regenerative Braking Strategy of Plug-in Hybrid Electric Vehicle

2010 ◽  
Vol 44-47 ◽  
pp. 1509-1513 ◽  
Author(s):  
Qing Sheng Shi ◽  
Xiao Ping Zhang ◽  
Fuan Chen
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Distribution Coefficients ◽  
Lookup Table ◽  
Regenerative Braking ◽  
Hybrid Electric ◽  
Braking Control ◽  
Novel Strategy

. In order to improve the energy efficiency of plug-in hybrid electric vehicles, it is important to design a suitable regenerative braking strategy. There are many control strategies that have been developed and presented for plug-in hybrid electric vehicles. Most of them are aimed to energy flow management, and seldom involves regenerative braking control. In this paper, a regenerative braking strategy based on multi-lookup table method is proposed for plug-in hybrid electric vehicles. Decelerations are introduced as the index of Table Selector, so braking force distribution coefficients can be flexibly adjusted using the proposed strategy. Finally, the simulation results show the validity of the novel strategy.

Multirate Integration in Hybrid Electric Vehicle Virtual Proving Grounds

1998 ◽  
Author(s):  
Dario Solis ◽  
Chris Schwarz
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Time Scales ◽  
Electric Vehicles ◽  
Time Scale ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Differential Algebraic Equations ◽  
Vehicle Systems ◽  
Hybrid Electric

Abstract In recent years technology development for the design of electric and hybrid-electric vehicle systems has reached a peak, due to ever increasing restrictions on fuel economy and reduced vehicle emissions. An international race among car manufacturers to bring production hybrid-electric vehicles to market has generated a great deal of interest in the scientific community. The design of these systems requires development of new simulation and optimization tools. In this paper, a description of a real-time numerical environment for Virtual Proving Grounds studies for hybrid-electric vehicles is presented. Within this environment, vehicle models are developed using a recursive multibody dynamics formulation that results in a set of Differential-Algebraic Equations (DAE), and vehicle subsystem models are created using Ordinary Differential Equations (ODE). Based on engineering knowledge of vehicle systems, two time scales are identified. The first time scale, referred to as slow time scale, contains generalized coordinates describing the mechanical vehicle system that includs the chassis, steering rack, and suspension assemblies. The second time scale, referred to as fast time scale, contains the hybrid-electric powertrain components and vehicle tires. Multirate techniques to integrate the combined set of DAE and ODE in two time scales are used to obtain computational gains that will allow solution of the system’s governing equations for state derivatives, and efficient numerical integration in real time.

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